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STACKING ENSEMBLE LEARNING AND INSTANCE HARDNESS THRESHOLD FOR BANK TERM DEPOSIT ACCEPTANCE CLASSIFICATION ON IMBALANCED …
Bank term deposits are a popular banking product with relatively high interest rates.
Predicting potential customers is crucial for banks to maximize revenue from this product …
Predicting potential customers is crucial for banks to maximize revenue from this product …
Development of Pre-Processing for Chronic Kidney Disease Prediction Using K-Nearest Neighbors Imputer and Chi-Square
R Mardianto, A Saikhu - 2024 8th International Conference on …, 2024 - ieeexplore.ieee.org
Chronic Kidney Disease (CKD) is a condition in which the function and/or structure of the
kidneys are severely damaged, resulting in an inability to filter blood as they should. This …
kidneys are severely damaged, resulting in an inability to filter blood as they should. This …
Classification of Darknet Traffic Using the AdaBoost Classifier Method
RE Sari, D Stiawan, N Afifah… - … Journal of Electrical …, 2024 - section.iaesonline.com
Darknet is famous for its ability to provide anonymity which is often used for illegal activities.
A security monitor report from BSSN highlights that 290.556 credential data from institution …
A security monitor report from BSSN highlights that 290.556 credential data from institution …
Implementation of Stacking Ensemble Learning for Bank Term Deposit Acceptance Classification
Accurately classifying bank term deposit acceptance is critical for optimizing marketing
strategies. This study proposes a novel Stacked Ensemble Learning (SEL) approach to …
strategies. This study proposes a novel Stacked Ensemble Learning (SEL) approach to …
Defending Against Local Adversarial Attacks through Empirical Gradient Optimization
B Sun, X Ma, H Wang - Tehnički vjesnik, 2023 - hrcak.srce.hr
Sažetak Deep neural networks (DNNs) are susceptible to adversarial attacks, including the
recently introduced locally visible adversarial patch attack, which achieves a success rate …
recently introduced locally visible adversarial patch attack, which achieves a success rate …
Analysis of Anomaly with Machine Learning Based Model for Detecting HTTP DDoS Attack
At present, almost every device is connected to the internet for communication. Information
also can be quickly obtained via the Internet. The Internet offers various helpful services like …
also can be quickly obtained via the Internet. The Internet offers various helpful services like …
Defending Against Local Adversarial Attacks through Empirical Gradient Optimization.
SUN Boyang, MA **aoxuan… - Technical Gazette …, 2023 - search.ebscohost.com
Deep neural networks (DNNs) are susceptible to adversarial attacks, including the recently
introduced locally visible adversarial patch attack, which achieves a success rate exceeding …
introduced locally visible adversarial patch attack, which achieves a success rate exceeding …
CURATING DATASETS TO ENHANCE SPYWARE CLASSIFICATION
Current methods for spyware classification lack effectiveness as well-structured datasets are
typically absent, especially those with directionality properties in their set of features. In this …
typically absent, especially those with directionality properties in their set of features. In this …
Farklı kodlama tekniklerinin KNN algoritmasının mantar sınıflandırma performansı üzerindeki etkisi
K İleri - Niğde Ömer Halisdemir Üniversitesi Mühendislik …, 2025 - dergipark.org.tr
In this study, the effects of different encoding techniques on the K-Nearest Neighbors (KNN)
algorithm in the classification of mushrooms as poisonous or edible were investigated …
algorithm in the classification of mushrooms as poisonous or edible were investigated …